In the present research,we describe a computer-aided detection(CAD)method aimed at automatic fetal head circumference(HC)measurement in 2D ultrasonography pictures during all trimesters of pregnancy.The HC might be ut...In the present research,we describe a computer-aided detection(CAD)method aimed at automatic fetal head circumference(HC)measurement in 2D ultrasonography pictures during all trimesters of pregnancy.The HC might be utilized toward determining gestational age and tracking fetal development.This automated approach is particularly valuable in low-resource settings where access to trained sonographers is limited.The CAD system is divided into two steps:to begin,Haar-like characteristics were extracted from ultrasound pictures in order to train a classifier using random forests to find the fetal skull.We identified the HC using dynamic programming,an elliptical fit,and a Hough transform.The computer-aided detection(CAD)program was well-trained on 999 pictures(HC18 challenge data source),and then verified on 335 photos from all trimesters in an independent test set.A skilled sonographer and an expert in medicine personally marked the test set.We used the crown-rump length(CRL)measurement to calculate the reference gestational age(GA).In the first,second,and third trimesters,the median difference between the standard GA and the GA calculated by the skilled sonographer stayed at 0.7±2.7,0.0±4.5,and 2.0±12.0 days,respectively.The regular duration variance between the baseline GA and the health investigator’s GA remained 1.5±3.0,1.9±5.0,and 4.0±14 a couple of days.The mean variance between the standard GA and the CAD system’s GA remained between 0.5 and 5.0,with an additional variation of 2.9 to 12.5 days.The outcomes reveal that the computer-aided detection(CAD)program outperforms an expert sonographer.When paired with the classifications reported in the literature,the provided system achieves results that are comparable or even better.We have assessed and scheduled this computerized approach for HC evaluation,which includes information from all trimesters of gestation.展开更多
Objective: To identify the impact of an abnormally large neonatal chest circumference relative to head circumference on labor and neonatal morbidity. Methods: We used a retrospective cohort design to study 54 obstetri...Objective: To identify the impact of an abnormally large neonatal chest circumference relative to head circumference on labor and neonatal morbidity. Methods: We used a retrospective cohort design to study 54 obstetric cases in which the neonatal thoracic circumference was ≥2.5 cm greater than that of the head. For each case we sought controls with a smaller thorax-head circumference difference. Ninety-seven controls were matched with their respective cases for birth weight, parity, maternal body mass index (BMI), and maternal ethnicity. Results: Cases had significantly smaller heads and larger trunks than controls (P < 0.0001). Cases were twice as likely (39% vs 19%, P = 0.007) to require admission to the neonatal intensive care unit. There was no significant difference between cases and controls in the frequency of shoulder dystocia, long second stage, or long deceleration phase of labor. However, compound presentations occurred more frequently in the cases than in controls (5.5% vs 0%, P = 0.044). Conclusion: Babies with disproportionately large trunk growth were at risk for requiring neonatal intensive care and for compound presentation.展开更多
提出一种超声图像中胎儿头围自动测量的新方法.利用机器学习的随机森林(random forests,RFs)算法自动检测感兴趣区域(region of interest,ROI),通过图像局部相位对称(phase symmetry,PS)检测头围边缘,使用非迭代椭圆拟合算法拟合出头围...提出一种超声图像中胎儿头围自动测量的新方法.利用机器学习的随机森林(random forests,RFs)算法自动检测感兴趣区域(region of interest,ROI),通过图像局部相位对称(phase symmetry,PS)检测头围边缘,使用非迭代椭圆拟合算法拟合出头围椭圆.与医生手动拟合测量的结果对比,145个头像的平均相对偏差为-3.86 mm,表明该方法可以鲁棒的自动检测胎儿头围.展开更多
文摘In the present research,we describe a computer-aided detection(CAD)method aimed at automatic fetal head circumference(HC)measurement in 2D ultrasonography pictures during all trimesters of pregnancy.The HC might be utilized toward determining gestational age and tracking fetal development.This automated approach is particularly valuable in low-resource settings where access to trained sonographers is limited.The CAD system is divided into two steps:to begin,Haar-like characteristics were extracted from ultrasound pictures in order to train a classifier using random forests to find the fetal skull.We identified the HC using dynamic programming,an elliptical fit,and a Hough transform.The computer-aided detection(CAD)program was well-trained on 999 pictures(HC18 challenge data source),and then verified on 335 photos from all trimesters in an independent test set.A skilled sonographer and an expert in medicine personally marked the test set.We used the crown-rump length(CRL)measurement to calculate the reference gestational age(GA).In the first,second,and third trimesters,the median difference between the standard GA and the GA calculated by the skilled sonographer stayed at 0.7±2.7,0.0±4.5,and 2.0±12.0 days,respectively.The regular duration variance between the baseline GA and the health investigator’s GA remained 1.5±3.0,1.9±5.0,and 4.0±14 a couple of days.The mean variance between the standard GA and the CAD system’s GA remained between 0.5 and 5.0,with an additional variation of 2.9 to 12.5 days.The outcomes reveal that the computer-aided detection(CAD)program outperforms an expert sonographer.When paired with the classifications reported in the literature,the provided system achieves results that are comparable or even better.We have assessed and scheduled this computerized approach for HC evaluation,which includes information from all trimesters of gestation.
文摘Objective: To identify the impact of an abnormally large neonatal chest circumference relative to head circumference on labor and neonatal morbidity. Methods: We used a retrospective cohort design to study 54 obstetric cases in which the neonatal thoracic circumference was ≥2.5 cm greater than that of the head. For each case we sought controls with a smaller thorax-head circumference difference. Ninety-seven controls were matched with their respective cases for birth weight, parity, maternal body mass index (BMI), and maternal ethnicity. Results: Cases had significantly smaller heads and larger trunks than controls (P < 0.0001). Cases were twice as likely (39% vs 19%, P = 0.007) to require admission to the neonatal intensive care unit. There was no significant difference between cases and controls in the frequency of shoulder dystocia, long second stage, or long deceleration phase of labor. However, compound presentations occurred more frequently in the cases than in controls (5.5% vs 0%, P = 0.044). Conclusion: Babies with disproportionately large trunk growth were at risk for requiring neonatal intensive care and for compound presentation.
